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The optimal Latin hypercube experimental design method is used to refine the vortex generator parameters, determine the test scheme, simulate and calculate the thrust and torque of the wind turbine, and obtain the experimental data. Based on the back propagation (BP) neural network, the aerodynamic performance model of the wind turbine vortex generator optimized by genetic algorithm is constructed. The reliability of the aerodynamic performance model is verified by calculating the error and root mean square of the predicted and simulated values of the aerodynamic performance model. Coupling the fish swarm algorithm and the aerodynamic performance model of the wind turbine vortex generator, an optimization method of the wind turbine vortex generator is established, and the height, length, and installation angle of the vortex generator are solved iteratively to realize the optimization of the vortex generator. The results show that compared with the original vortex generator scheme, the flow separation of the wind turbine blade section optimized by the vortex generator is effectively restrained and delayed, the surface fluid separation phenomenon is improved, the power of the wind turbine is increased by 1.711%, and the thrust of the wind turbine is decreased by 0.875%.